Anonymization means to remove personal identifier or converted into non readable form by human to protect private or personal information. Data anonymization can be performed in different ways but in this paper k-anonymization approach is used. Suppose one person A having his own kanonymous database and needs to determine whether database is still k-anonymous if tuple inserted by another person B. For some applications (for example, Students record), database needs to be confidential, So access to the database is strictly controlled. The confidentiality of the database managed by the owner is violated once others have access to the contents of the database. Thus, Problem is to check whether the database inserted with the tuple is still k-anonymous without letting the owner A and others (B) to know the content of the tuple and database respectively. In this paper, we propose a protocol solving this problem on suppression based k-anonymous and confidential database

1. Integrated Intelligent Research(IIR) International Journal of Business Intelligent
Volume: 01 Issue: 02 December 2012,Pages No.28-31
ISSN: 2278-2400
28
Protecting Privacy When Disclosing Information:
K Anonymity and its Enforcement Through
Suppression
V. Khanaa1
, R. Udayakumar2
Dean-Information., Bharath University ,
Asst.Prof.,IT. Bharath University
Email:drvkannan62@yahoo.com, ruskumar2007@hotmail.com
Abstract-Anonymization means to remove personal identifier
or converted into non readable form by human to protect
private or personal information. Data anonymization can be
performed in different ways but in this paper k-anonymization
approach is used. Suppose one person A having his own k-
anonymous database and needs to determine whether database
is still k-anonymous if tuple inserted by another person B. For
some applications (for example, Students record), database
needs to be confidential, So access to the database is strictly
controlled. The confidentiality of the database managed by the
owner is violated once others have access to the contents of the
database. Thus, Problem is to check whether the database
inserted with the tuple is still k-anonymous without letting the
owner A and others (B) to know the content of the tuple and
database respectively. In this paper, we propose a protocol
solving this problem on suppression based k-anonymous and
confidential database.
I. INTRODUCTION
For each application database is important or valuable thing, so
their security is important. There are different security control
methods are identified and each method have different criteria.
For example, FERPA provides privacy protections for such
records when held by federally funded educational
institutions[1]. FERPA defines an education record as those
records, files, documents, and other materials that contain
information directly related to a student and are maintained by
an educational agency or institution or by a person acting for
such agency or institution. Students who are at least 18 years of
age, or attending postsecondary institutions or otherwise their
parents ,generally have a right to gain access to their education
records within 45 days of a written request, seek to amend any
information therein considered to be in error, control how
information in such records is disclosed to other institutions ,in
general, such disclosures must be authorized by the student or
parent, with some exceptions and complain to the US
Department of Education if these rights appear to have been
violated. There is problem of providing security to statistical
databases against disclosure of confidential information. There
are various security control method classified into four groups:
conceptual, query restriction, data perturbation, and output
perturbation. Criteria for evaluating the performance of the
various security-control methods are identified. A detailed
comparative analysis of the most promising methods for
protecting dynamic-online statistical databases is also
presented. To date no single security-control method prevents
both exact and partial disclosures. There is big concern for
privacy. The problem of statistical disclosure control revealing
accurate statistics about a population while preserving the
privacy of individuals has a vulnerable history. Still, there is a
difference between confidentiality and privacy- Confidentiality
refers to limiting information access and disclosure to
authorized users and preventing access by or disclosure to
unauthorized users. Privacy refers to limiting access to
individuals' personal information[5].Question is
Confidentiality is still required if data have been anonymized-
yes because anonymous data have business value for the party
owning database or unauthorized disclosure of anonymous data
may damage the party owning the data. There have been lots of
techniques developed to protect privacy, but here we proposed
k-anonymization [4]. K-Anonymity refers to attributes are
suppressed or generalized until each row is identical with at
least k-1 other rows. At this point the database is said to be k-
anonymous. K-Anonymity prevents definite database linkages.
The modification of the anonymous database DB can be
naively performed as follows: the party who is managing the
database or the server simply checks whether the updated
database DB is still anonymous. Under this approach, the
entire tuple t has to be revealed to the party managing the
database server, thus violating the privacy of the patient.
Another possibility would be to make available the entire
database to the patient so that the individual can verify if the
insertion of the data violates their own privacy. This approach
however, requires making available the entire database to the
patient thus violating data confidentiality. There is a protocol
solving this problem on suppression-based k-anonymous and
confidential databases. The protocol depends on well-known
cryptographic assumptions. The huge numbers of databases
recording a large variety of information about individuals
makes it possible to find information about specific individuals
by simply correlating all the available databases.
Confidentiality is achieved by enforcing an access policy, or
possibly by using some cryptographic tools. Privacy relates to
data can be safely disclosed without leaking sensitive
information regarding the legitimate owner. The confidentiality
is still required once data have been anonymized, if the
anonymous data have a business value for the party owning
them or the unauthorized disclosure of such anonymous data
may damage the party owning the data or other parties. So,
problem is that can database owner assure privacy of database
without knowing data to be inserted? It is important to assure
that database maintains privacy of individual and also who
maintain database. So, it needs to check that data entered in

2. Integrated Intelligent Research(IIR) International Journal of Business Intelligent
Volume: 01 Issue: 02 December 2012,Pages No.28-31
ISSN: 2278-2400
29
database do not violate privacy, and to perform such
verification without seeing sensitive information of individual.
II. KEY CHALLENGES
There are some limitations of the protocol, if the database is
not anonymous with respect to a tuple that has been inserted,
the insertion cannot be performed. Therefore, one of the
protocols is extremely inefficient. There are efficient protocols.
The first research is based on algorithms for database
anonymization. The database is protected by data reduction,
data perturbation or generating synthetic data. However, the
main concept of k-anonymity to maintain confidentiality of
their contents. The problem is to protect privacy of data that
has been divided into two groups depending on whether data
are continuously released and anonymized or data released in
different fashion and anonymized. The second research is
related to Secure Multiparty Computation protocol which is
subfield of cryptography. The third research is related to the
private information retrieval, which can be seen as an
application of the secure multiparty computation techniques to
the area of data management. This allows a user to retrieve an
data (or tuple) from database without revealing tuple one is
retrieving. Here, main focus is to find efficient techniques to
express queries over a database without letting the database
know the actual queries [2]. Still, the problem of private
updation of database has not been resolved because these
techniques deal with only data retrieval. These approaches that
will not address the problem of k-anonymity since their goal is
to encrypt the data hence external entities can obtain their data.
Thus, the main goal is to protect the confidentiality of the data
from the external entities that manages the data. Even though,
the data are fully available to the clients that are not the case
under our approach. In data anonymization, Insertion cannot be
performed if database is not properly anonymized. The
problem is private updates to k-anonymous databases The
suppression based protocols deals with the problem of updating
the databases. Figure 1 shows Anonymous database system, we
assume that information of single student stored in a tuple and
database kept confidential at server.
The users treated as database of educational record, only
institution have right to access to database. Since database is
anonymous, the data provider’s privacy is protected from
users. Since database have privacy sensitive data, so main aim
to protect privacy of student’ data. This can be achieved by
anonymization. If database is anonymous, it is not possible to
catch student’s identity for database. Suppose new student has
to be entered, this means database has to be updated in order to
insert a tuple. The modification of anonymous database can be
done as follows: the party who is managing the database
checks whether the updated database is still anonymous after
inserting a tuple. Under this approach, the entire tuple t has to
be revealed to the party managing the database server, thus
violating the privacy of the student. Another possibility would
be to make available the entire database to the student so that
the student can verify by himself/herself if the insertion of
his/her data violates his/her own privacy. To get solution of
these problem, several problem needs to be addressed: The first
problem is: without revealing the contents of tuple t to be
inserted and database DB, how to preserve data integrity by
establishing the anonymity of DB U {t}.The second problem
is: once such anonymity is established, how to perform this
update?
The third problem is: what can be done if database anonymity
is not preserved? Finally, the forth problem is: what is the
initial content of the database, when no data about users has
been inserted yet? In this paper, we propose a protocol solving
first Problem, which is the central problem addressed by our
paper.
III. DEVELOPMENT OF LINGUISTIC
RESOURCE
The protocol relies on the fact that anonymity of database does
not affected ,if inserting tuple is already in database. then ,the
problem of integrity while inserting tuple in database is
equivalent to privately checking of inserting tuple with tuple
already in database. The protocol is aimed at suppression based
anonymous database and it allows the owner of database to
properly anonymize the tuple t, without gaining any useful
knowledge on its contents and without having to send to its
owner newly generated data. To achieve such goal, the parties
secure their messages by encrypting them. To assure higher
level of anonymity to the party inserting a tuple ,we require
that the communication between the party and database occurs
through anonymous connection, as provided by crowd
protocol[3]. Crowd protocol hides each user's communications
by routing them randomly within a group of similar users. In
order to perform the privacy-preserving verification of the
database anonymity upon the insertion, the parties use a
commutative and homomorphic encryption scheme.
Prototype Architecture
In the above figure, Data provider enters data is stored in
crypto module which perform cryptography operation on all

3. Integrated Intelligent Research(IIR) International Journal of Business Intelligent
Volume: 01 Issue: 02 December 2012,Pages No.28-31
ISSN: 2278-2400
30
tuples exchanged between user and Private updater, using
suppression based method. Loader module read anonymized
tuples from k-anonymous database. And checker module
checks whether the tuple from the user matches with the tuple
in the database. If none of the tuple matches with the user
tuple, then loader reads another tuple from k-anonymous
database. The functionality provided by the Private Checker.
Communication between user and database is carried out by
anonymizer and that all the tuples are encrypted.
IV. SUPRESSION BASED PROTOCOL
Suppression based protocol relies on well-known
cryptographic techniques. We consider table T={t1,…t2} over
the attribute set A. Generally in suppression based method we
mask value of some special attributes with *, the value
deployed by the user for anonymization. So the main idea
behind this protocol is: To form subset of indistinguishable
tuples by masking the value of some well chosen attributes.
TABLE 1 Original Dataset
Birth date Sex Zip code
21/1/79 male 53715
10/1/79 female 55410
21/2/83 male 02274
19/4/82 male 02237
TABLE 2 Suppressed Data with k=2
Birth date Sex Zip code
*/1/79 person 5****
*/1/79 person 5****
*/*/8* male 022**
*/*/8* male 022**
As shown in table 1 which contains original database (Table T)
having three attributes Birth date, Sex, Zipcode. Table 2 shows
a suppression based k-anonymization with k=2.As shown in
table k=2 means at least k(=2) tuples should be
indistinguishable by masking values. Suppression based
attributes for every tuple of T is referred as anonymization
problem, and finding the anonymization that minimizes the
number of masked values.
A. Cryptography Primitive
The Diffie Hellmen key exchange algorithm allows two users
to establish shared secret key over insecure communication
without having any prior knowledge. Here, Diffie Hellmen is
used to agree on shared secret key to exchange data between
two parties. AES(Advanced Encryption Standard) algorithm is
the advanced encryption standard form of algorithm which had
been used as a symmetric form of encryption.
There are two encryption schemes, commutative and product
homomorphic E to satisfy indistiguishability properly.. A
commutative, product- homomorphic encryption scheme
ensures that the order in which encryptions are preformed is
irrelevant(commutativity) and it allows to consistently perform
arithmetic operations over encrypted data (homomorphic
property). Given a finite set K of keys and a finite domain D, a
commutative, product homomorphic encryption scheme E is a
polynominal time computable function E: K×D→D satisfying
the following properties:
1. Commutativity:
In commutative, all key pairs 𝑘1,2∈𝑘 and value 𝑑∈𝐷, the
following equality holds: 𝐸𝑘1 𝐸𝑘2 𝑑 =𝐸𝑘2(𝐸𝑘1(𝑑))
2. Product-homomorphism:
In product homomorphic every 𝑘∈𝑘and every value pairs
𝑑1,2∈𝐷 the following equality holds: 𝐸𝑘 𝑑1 ∙𝐸𝑘 𝑑2
=𝐸𝑘(𝑑1∙𝑑2)
3. Indistinguishability:
It is infeasible to distinguish an encryption from a randomly
chosen value in the same domain and having the same length.
The advantages are high privacy of data even after updation,
and an approach that can be used is based on techniques for
user anonymous authentication and credential verification.
B. Algorithm
Suppose Alice has control over database and Bob is data
provider then protocol works as follows: In step 1, Alice sends
Bob encrypted version of tuple containing only non suppressed
attributes. At step 2, bob encrypts the information received
from Alice and sends it to her, along with encrypted version of
each value in his tuple. In final step, Alice examines if the
suppressed attributes of tuple is equal to the tuple sent by Bob.
If yes then insert tuple in database.
V. RELATED WORK
In this paper, we have proposed secure protocol for privately
checking whether a k-anonymous database retains anonymity
once a new tuple is being inserted to it. Since the proposed
protocol ensures the updated database remains k-anonymous.
Thus the database is updated properly using the proposed
protocol. The data provider’s privacy cannot be violated if user
update a table. If updating any record in database violate the
k- anonymity then such updating or insertion of record in table
is restricted. If insertion of record satisfies the k-anonymity
then such record is inserted in table and suppressed the
sensitive information attribute by * to maintain the k-
anonymity in database. Thus by making such k-anonymity in
table that makes unauthorized user to difficult to identify the
record. The important issues for future work are as follows:
i. Improve the efficiency of protocols, by the number of
messages exchanged and sizes and algorithm used for
encryption and decryption.
ii. The private update to database systems techniques
supports notions of anonymity different than k-
anonymity.
iii. In the case of malicious parties by the introduction of
an untrusted third party, implementing a real-world
anonymous database system.

4. Integrated Intelligent Research(IIR) International Journal of Business Intelligent
Volume: 01 Issue: 02 December 2012,Pages No.28-31
ISSN: 2278-2400
31
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